J. Bio. & Env. Sci. 2014

141 | Akbari et al

RESEARCH PAPER OPEN ACCESS

Assessment of genetic diversity of iranian population of

Anethum graveolens L. (dill) using AFLP molecular markers

Hariri Akbari F.1*, Omidi M.2, Torabi S.3, Khoshkharam M. 4, Bovard R.1, Shafiee M.5,

Safakish kashani MB. 6, Saeed P. 7 , Behjat Sasan, B.8

1 Department of Agricultural Biotechnology, Islamic Azad University, Research and Science Branch,

Tehran, Iran

2 Department of Agronomy and Plant Breeding, Faculty of Agriculture, Tehran

University, Karaj, Iran

3 Department of Agriculture and Plant Breeding, Faculty of Agriculture, Islamic Azad University,

Research and Science Branch, Tehran, Iran

4 Department of Agronomy, Islamic Azad University, Khorasgan Branch, Isfahan, Iran

5 Department of Biotechnology, Zabol University, Zabol, Iran

6 Department of Agronomy, Tehran University, Karaj, Iran

7 Department of Gardening, Zabol University, Zabol, Iran

8 Department of Horticultural, Islamic Azad University, Research and Science Branch, Tehran, Iran

Article published on June 12, 2014

Key words: AFLP markers, genetic diversity, Anethum graveolens L. (dill).

Abstract

Anethum graveolens L. (dill) is an important medicinal and industrial plant. The essential oil of this species is

used in different industrial such as pharmacy, nutrition, perfume manufacturing and veterinary. The populations

collected from different regions of the country were cultivated in order to investigate the genetic diversity of dill

and were studied in aspect of genetic variation and its correlation with geographical distribution. 337 alleles were

observed polymorphic and 108 alleles in monomorphic of total 455 scorable alleles. Percentage of polymorphic

bands was equal to 74 and the number of alleles observed for each primer combination ranged from 18 to 60. The

highest number of alleles was associated with M22-E2 and E11-M17 primer and the lowest value was observed in

E2-M35 primer combination. The coefficient of genetic similarity was varied between genotypes from 56/0 to

88/0. The minimum of genetic similarity was between populations of Shahrekord, Ahvaz and Yasuj with

Journal of Biodiversity and Environmental Sciences (JBES) ISSN: 2220-6663 (Print) 2222-3045 (Online)

Vol. 4, No. 6, p. 141-152, 2014

http://www.innspub.net

J. Bio. & Env. Sci. 2014

142 | Akbari et al

similarity coefficient 34%. The maximum of similarity was observed among samples of 17 and 18 that genetic

difference was very little and almost zero between them. Cluster analysis of populations using UPGMA algorithm

and SM indicated high genetic diversity among populations of dil and also no correlation between molecular

diversity and geographic distribution. The existence of genetic diversity in these samples confirms that the

phytochemical and morphological differences of the samples is not simply due to environmental impacts, but are

controlled by genetic factors as well. The results of this study can be useful in the management of germplasm of

dill.

*Corresponding Author: Hariri Akbari F Hariri.a.farhad@gmail.com

Introduction The use of medicinal plants is very valuable as major

and minor products in Iran and elsewhere in the

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143 | Akbari et al

world. Clearly, determination of these plants genetic

characteristics, morphological, physiological, bio-

chemical and ecological of these plants in order to

sustainable utilization of economic, health and

sanitary goals and also maintaining diversity in

natural areas and preventing the extinction of

endangered plant is necessary. On the one hand the

medicinal plants are increasingly important due to

secondary metabolite components, but on the other

hand nowadays it is essential to find alternative

sources in order to maintain health and reduce the

harmful effects of chemicals because of pathogen

resistance against the existing drugs and antibiotics

(Hariri Akbari et al., 2010; Karimi, 1998).

In the past two decades, biotechnology in agriculture

has provided promising prospects. The increasing

development of biotechnology science in the twenty-

first century in any country has lead to the

development and progress of science, industry and

the economy of that country. In the meantime,

molecular discussions have growing importance in

biology studies.

Medicinal plants are the main storage resources of

medicinal compounds which about 80% of the world

population still need the resources to maintain their

health and sanitation. Plant secondary metabolites

have great economic importance as pharmaceuticals,

aromatic compounds, pigments, food additives and

etc. (Hariri Akbari et al., 2012).

Biotechnology tools are very useful and significant in

selection, reproduction, analysis, increasing and

improving the metabolite compounds of medicinal

plants. Genetic engineering and genetic

manipulation, particularly with the use of indirect

methods (bacteria) and direct (gene transfer in

plants), are powerful tools in order to produce new

secondary metabolites (Hariri Akbari et al., 2010).

Functional and comparative genomics, have provided

the efficient and convenient tools such as Expressed

Sequence Tags (EST), micro-arrays (Microarray) and

molecular markers that can examine expression

patterns of several genes (hundreds of genes) and the

mechanism regulating the expression of these genes

in a short time, even at a time. Nowadays it has

increased our understanding of the interaction

between genes and biosynthesis pathway and

production of biochemical compounds in plants. Also

it has made more efficient breeding programs in the

germplasm by determining the relationships and

interval genetic (Kamalodini et al., 2006; Hariri

Akbari et al., 2010).

Green leafy vegetables are good sources of minerals as

well as vitamins. Anethum graveolens L. (dill) a green

leafy, widespread vegetable belongs to the family

Apiaceae (Umbelliferae) that has an attractive flavor

(Cankur et al., 2006). From 1500 BC, dill was

considered as analgesic and the only species of the

genus which cultivated in Iran is Anethum that have

been found in temperate regions of Europe

(Mediterranean and West Asia) (Majnoon Hosseini

and Davazdah Emami, 2007).

The origins of dill have been attributed to the eastern

Mediterranean and Europe (Zohary and Hopf,

2000).This plant has an old long history in many

countries and cultures. Earliest source obtained

indicates that, this plant has been used as an

analgesic in 5000 years ago in ancient Egypt (Omid

Baigi, 2006; Zargari, 1996; Yazdani et al., 2005).

The essential oils of this species has limonene (20 -

28%), Terpinene or α-Phellandrene, b- Phellandrene,

Alpha-pinene, Parasmyn, myristicin (0.062 %),

Carvone, Dill ether, myrcene (40 - 60%). Carvone is

the main component of the essential oils in this plant

among the others (Kamalodini et al., 2006; Yazdani

et al., 2004). The composition of dill essential oil

changes markedly through the growing season. The

characteristic of dill oil depends largely on the ratio of

carvone and a-phellandrene (Callan et al., 2007).

From old times dills have been used to treat some

digestive disorders such as bloating, indigestion and

ulcers of the stomach and intestines] (Kobayashi and

Kamata, 1999; Haji sharify, 2005). Dills are inhibitors

on the enzyme Lipoxyginese due to the presence of

J. Bio. & Env. Sci. 2014

144 | Akbari et al

flavonoids. That is why is used as a lipid- lower blood

drug. Limonene in dill) is used in the perfume

manufacturing, cosmetics, Colorful soaps, deodorant,

spice, resins manufacturing and moisturizer

(Barghamady, 2006; Haji sharify, 2005).

Furocoumarins components of this plant cause

genetic mutations. These components exist in some

plant species, particularly in Family Apiaceae and

interact in the presence of activated UV light and with

vital macromolecules such as DNA and RNA (Zolala,

2008). It has been reported that it is a possible source

of antioxidant and also has anti-microbial properties

against Rhodotorula glutinis, Aspergillus ochraceus

and Fusarium moniliforme (Cankur et al., 2006;

Nanasombat and Wimuttigosol, 2011).

Recently, molecular methods have been used for the

identification and classification of different species of

herbs and medicinal plants (Yu et al., 2011). The

study of genetic diversity is the first step of a breeding

program and genetic resources that are very valuable

for breeders (Papini et al., 2007). Genetic variation

might be evaluated by assessing morphological or

biochemical traits but molecular markers In

particular, DNA-based markers provide the best

assessment of genetic variation because they are

plentiful and are not dependent on environ-mental

effects. This made this evaluation more efficient and

reliable (Dongre et al., 2007; Fu et al., 2003).

After the development of polymerase chain reaction

(PCR) technology (Etminan et al., 2012), several

PCR-based markers were developed and applied to

assess the genetic variation among populations and

genetic resources. These marker systems are different

in technical principle, type of inheritance,

reproducibility, amount of polymorphism and in their

costs (Etminan et al., 2012).

Several PCR-based markers were developed and

applied to assess the genetic variation among

populations and genetic resources. These marker

systems are different in technical principle, type of

inheritance, reproducibility, amount of

polymorphism and in their costs (Schulman, 2007).

The amplified fragment length polymorphism (AFLP)

technique (Vos et al., 1995) is one of the best marker

systems that can be used to detect high levels of DNA

polymorphism and is extremely promising for genetic

diversity studies (Etminan et al., 2012).

The objective of this study was to estimate the genetic

diversity among the 42 Iranian populations of

Anethum graveolens L. (dill) using the Amplified

Fragment Length Polymorphism (AFLP).

Table 1. changes Comparison of five main

components of Anethum at different stages of growth

(percent) (Yazdani et al., 2004)

compounds Dill-1 Dill-2 Dill-3

-phellandrene 19.2 6.49 5.63

Limonene 14.21 17.71 15.54

Dill ether 15.69 2.74 1.49

Carvone 48.82 64.86 64.62

trans-dihydrocarvone 2.22 6.64 10.60

Sum total 89.14 97.42 98.19

Dill-1: The flowering stage and Beginning of seed

formation

Dill-2: seed formation before fully ripening

Dill-3: full ripening

Materials and methods

Plant material and collecting population of Anethum

graveolens L. (dill)

42 populations were collected from different cities of the

country. And cultivated in order to perform tests and

take samples in the Research farm of Institute of

Medicinal Plant, Karaj, Iran. In order to achieve accurate

and comprehensive information regarding to Iranian

Populations of dill, we have attempted that collected

populations to be appropriate for the geographic

distribution throughout the country (tabe 2).

Table 2. Origin of collecting Samples

Number of

sample

Origin of collecting samples

Number of

sample

Origin of collecting samples

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145 | Akbari et al

1 Urmia 22 Abadeh

2 Ajab Shir 23 Bandar Abbas

3 Tabriz 24 Qeshm

4 Ardabil 25 Bojnord

5 Tehran 26 Arak

6 Lahijan 27 Quchan

7 Kermanshah 28 Nishapur

8 Eslamabad-e

Gharb 29 Kashmar

9 Zanjan 30 Zoeram, Shirvan

10 Karaj 31 Gonabad

11 Arak 32 Birjand

12 Varamin 33 Zabol

13 Delijan 34 Baft

14 Kashan 35 Sari

15 Isfahan 36 Qaem Shahr

16 Najafabad 37 Dorud

17 Shahrekord 38 Semnan

18 Ahvaz 39 Yazd

19 Yasuj 40 Shiraz 2

20 Marvdasht 41 Rudehen

21 Shiraz 1 42 Tehran

Plant cultivation and production of plant material

First the seeds were collected from plants of natural

habitats. The seeds were put in Petri dishes on wet

filter paper and transferred to plastic pots after

germination in order to grow these plants to a height

of 10 to 15 cm and also leaves grow enough. After

three weeks, fresh leaves from each pot were picked

for genomic DNA extraction.

Genome extraction and purification

Total genomic DNA was extracted and the quality of

the extracted DNA was tested on 1% agarose gel

electrophoresis and quantity was measured with a

spectrophotometer (Hariri Akbari et al., 2012). The

fresh and young leaves of each sample produced in a

mortar were ground to a fine powder in liquid

nitrogen, and transferred to the tubes 1/5 ml. 900 µl

of SDS 4% extraction buffer was added per tube and

placed for 45 Min in water bath at 65 ° C. and then

added 300 µl of potassium acetate per tube for 25

Min under ice container. The tubes were centrifuged

at a temperature of 3 ° C for 15 Min and at 12000

rpm. 750 µl of the upper liquid transferred to a new

tube and 750 µl of cold isopropanol added to it and

placed 5 Min at laboratory temperature (25 ° C). Then

the tubes were centrifuged at a temperature of 3 ° C

for 15 Min and at 12000 rpm and after removing

supernatant and tubes containing plates were

incubated at 37 ° C for 20 to 30 Min. In order to

purify, 700 µl of autoclaved deionized -distilled water

(DDW) was added to each tube that has been kept for

1 h at 4 ° C. and then added the chloroform isoAmyl

alcohol solution (24:1) volume of 700 µl and shaken

well until a uniform emulsion was obtained.

Centrifugation was performed for 10 Min at 13000

rpm, the lower phase is chloroform Isoamyl alcohol

and upper phase is solution containing DNA. The

upper phase are transferred to a new 2 ml tube and

was added 0/1 volume of sodium acetate supernatant

liquid (3 M, pH =8). Absolute alcohol (100%) that is

2/5 times volume of supernatant liquid was added

and then dehydrated after 5 Min. centrifuge was

performed for 10 Min at 13000 rpm and discarded

the supernatant liquid and added 100 ml 70% alcohol

to the sediment. The alcohol was removed and the

samples incubated at 37 ° C for 20 to 30 Min to dry

completely and then added TE buffer (100 µl) or

deionized -distilled water (DDW). The quality of the

extracted DNA was tested on 1% agarose gel

electrophoresis and quantity was measured with a

spectrophotometer.

AFLP assays

The AFLP procedure was performed with appropriate

modifications of the method described by Vos et al.,

(1995).

Enzyme digestion and ligation of adapters

Genomic DNAs Concentration was reached to 250 Ng

/ µl by dilution. To perform double digestion with

EcoRI and MseI restriction enzymes were used as

follows: 2.5 unit of each restriction enzyme, 4 μl

Tango buffer (10x), Template DNA: 10 μl of genomic

DNA (250 ng) of each sample, DDW:10 µL] In the

following, reaction components were placed in for 3 h

at 37 ° C. and kept for 1 h at 65 ° C. respectively and

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146 | Akbari et al

treated at laboratory temperature for one day

(Etminan et al., 2012; Vos et al., 1995).

The digested fragments were ligated to double

stranded adaptors appropriate with the EcoRI and

MseI restriction sequences, the process of ligation of

adapters were performed as follows: adding

connection components to each tube that contain

Buffer Ligase 10x: 1µL E.Adaptor

(CTCGTAGACTGCGTACC): 1µL, M. Adaptor

(GACGATGAGTCCTGAG): 1.5 unit T4 DNA ligase to

materials derived from the digestion of the reaction

components at 25 ° C for 4 h and then maintaining 24

h at 37 ° C. The ligated DNA fragments were diluted

three times with sterile distilled water and stored at -

20°C. (Vos et al., 1995).

Preamplification and selective amplification

Preamplification was carried out using non-selective

primers E000 and M000 (Table 3) in a 25 μl reaction

volume containing 3.75 μl of (1:3) diluted ligation

product, 1 unit of Taq polymerase, 1X Taq polymerase

buffer, 0.4 μM of each of the two primers, 150 μM of

each of dATP, dCTP, dGTP and dTTP, and 2 mM

MgCl2. This amplification was performed in a

thermocycler programmed for 25 cycles, each

consisting of 1 min at 94°C, 1 min at 60°C and 72°C

for 2 min. The final extension was done at 72°C for 7

min. The pre-amplification product was diluted 1:9 in

sterile double distilled water to prepare template

DNA for selective amplification (Etminan et al., 2012;

Vos et al., 1995).

Selective proliferation stage was performed using 15

different combinations (Table 3) of primers, Selective

amplification was performed in a 25 μl reaction

mixture volume containing 3.75 μl of diluted pre-

amplification product, 1x Taq polymerase buffer, 2

mM MgCl2, 1 Unit of Taq polymerase, 150 μM of

dNTPs, and 0.4 μM of each of the two primers with

two or three additional nucleotides at the 3´end. For

the selective amplification step, the following cycle

profile was used: 5 min at 94°C for pre-denaturing, 35

consecutive cycles each consisting of 1 min at 94°C for

denaturing, 1 min at 65°C for annealing and 2 min at

72°C for extension. After these 35 cycles, a final

extension step was done at 72°C for 7 min. 15 primer

combinations were used for diversity assessment. The

PCR products were separated on denaturing 6% (w/v)

polyacrylamide gel electrophoresis. For amplified

fragment detection, silver staining method was used

as described by Etminan et al., (2012) and Vos et al.,

(1995).

Table 3. primers names and sequence

Primer sequence Primer name

E4 ׳GAC TGC GTA CCA ATT CGT C-3-׳5

E11 ׳GAC TGC GTA CCA ATT CAG G-3-׳5

E8 ׳GAC TGC GTA CCA ATT CAC T-3-׳5

E2 ׳GAC TGC GTA CCA ATT CAA C-3-׳5

ETG ׳GAC TGC GTA CCA ATT CTG-3-׳5

M35 ׳GAT GAG TCC TGA GTA AGA G-3-׳5

M22 ׳GAT GAG TCC TGA GTA ACC C-3-׳5

M20 ׳GAT GAG TCC TGA GTA ACA T-3-׳5

M17 ׳GAT GAG TCC TGA GTA ACA A-3-׳5

E000 ׳GAC TGC GTA CCA ATT C-3-׳5

M000 ׳GAT GAG TCC TGA GTA A-3-׳5

Band scoring and statistical analysis

Obtained gels were scored for each primer pair after

recording the information. Presence of band was

considered as 1 and absence of band as 0 respectively

(Negi et al., 2006). Variables of each primer were

placed in a row and name of genotypes in the column

by using Microsoft Excel software. The similarity

matrix and cluster analysis was performed using

NTSYS-pc analytical software v.2. and dendrogram

was constructed based on DICE similarity coefficient

and the accessions were grouped by cluster analysis

using the UPGMA algorithm method. To determine

the correlation between similarity matrices and

cophenetic, Mantel test was used that MAXCOMP

coefficient obtained via COPH and SM coefficients

was applied for the Mantel test (Powell et al., 1996).

Results

The results of AFLP reaction

Molecular markers, in particular DNA based markers

provide reliable genetic information because of the in-

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147 | Akbari et al

dependence of the confounding effects of

environmental factors (Powell et al., 1996). 15 AFLP

primer combinations were used to investigate genetic

diversity of 42 populations of dill samples. In total

455 entirely specific and scorable bands were

recorded that 337 polymorphic bands were observed.

This amount includes 74/06% of all observed bands.

The number of bands varied from 18 to 60 per

primer. Maximum and minimum of observed bands

was associated with primer E11-M17, M22-E2 with 60

bands and E2-M35 primer with an 18 bands

respectively (Fig. 1). The average number of bands

was 33/30 per primer. But maximum and minimum

of polymorphism was the primers E11-M17 with 34

bands and E2-M35 with 18 observed bands

respectively, and also the average of polymorphic

bands were 46/22 (table 4).

Table 4. Primer combinations, the total number of bands for each primer, the number of polymorphic bands and

percentage of polymorphism

Percentage of polymorphism

Number of polymorphic bands

total number of bands

Primer combination Row

89/2 25 28 E11-M35 1

85/7 24 28 E46-M17 2

53/3 16 30 E46-M20 3

80/7 21 26 E46-M22 4

100 25 25 E8-M20 5

72/2 13 18 E46-M35 6

92 23 25 E11-M22 7

50 30 60 E2-M22 8

56/99 34 60 E11-M17 9

64 32 50 E8-M17 10

85 17 20 E11-M20 11

86/3 19 22 E2-M17 12

100 18 18 E2-M35 13

92 23 25 E2-M20 14

85 17 20 E8-M35 15

74/06 337 455 Et-Mt Total

Fig. 1 Polymorphism Investigation of Iranian

Anethum graveolens L. (dill) by using primers E2-

M22. In this sample the total number of bands were

60, number of polymorphic bands were 30 and

polymorphism percent was 50%.

Cluster analysis

These values were arranged in a symmetrical matrix

of genetic tree similarity based on UPGMA algorithms

for clustering in NTSYS-pc software and cluster

diagram was drawn. Degree of genetic similarity

between genotypes varied from 54% to 88%. The

lowest similarity between sample numbers 17

(Shahrekord) and 18 (Ahvaz) with Yasuj (19) about

34% and the highest similarity about 88% were

between samples 17 and 18 (Fig. 2).

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148 | Akbari et al

Fig. 2 Cluster diagram of 42 Anethum graveolens L. (dill) based on 15 different primer combinations with an

Analytical method (UPGMA)

The results of Mantel test

In general, a cluster diagram doesn’t indicate the

accuracy of the obtained results, so Mantel test was

used for determining the correlation between the

similarity matrix and cophenetic correlation.

Therefore the results of Mantel test was obtained

from principal components analysis and the purpose

of this calculation is to identify the parameters that

firstly include all aspects of information that

contained original data and secondly the numbers of

data be fewer than the number of main variables

(Martinez et al., 2003; Negi et al., 2006).

To this end, molecular and genetic similarity values

and Individuals genealogy were arranged as

corresponding in format of matrix and compared with

software MAXCOMP (Negi et al., 2006).

Therefore cophenetic correlation coefficient (r) was

used and converted to its equivalent for calculating

the dendrogram, and then the cophenetic matrix was

compared with the similarity matrix. The obtained

clustering graph had cophenetic coefficient r=0/79.

In molecular studies, high cophenetic coefficient is a

factor for efficiency of obtained diagram. On the other

hand low cophenetic coefficient could not be a reason

for of inefficiency of obtained diagram, but low

cophenetic correlation coefficient may be due to

unusual circumstances in the data, in particular on

molecular data (Khunani, 2008) (Fig. 3).

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149 | Akbari et al

Fig. 3 graphics resulting from Mantel test were obtained using COPH and SM Pearson coefficients MAXCOMP

and confirms Cluster analysis resulting from UPGMA cluster analysis.

Discussion

The results showed that AFLP molecular markers are

useful tools for studying the genetic diversity of

medicinal plants like dill. The results of other studies

have revealed that several factors have affected

estimation of genetic relationships among individuals

that some of them include the number of markers

have been used, distribution of the markers in the

genome and the nature of evolution mechanisms that

basis for causing diversity (Rezaei et al., 2012;

Kermani et al., 2006).

It should be noted about the number of markers that

the amount of information acquired from AFLP

method highly depend on the number of used primer

combinations but ( Ellis et al 1977) showed that it is

possible to explain 80% of the genetic relationships

with choosing the 6 combinations of the best primers

(Khunani, 2008).

Study of genetic diversity in the family Apiaceae using

molecular markers has been reported in Changium

smyrnioides (RAPD) by (32), Carum L. (Santos and

Simon, 2002) and carrot (AFLP) by Negi et al., (2006).

As regard to this subject, in this study it has been used 15

AFLP primer combinations (table 4) and analysis of

banding patterns of revealed 337 polymorphic bands

that with an average of 22.467 fragments per each

primer combination. The maximum and the minimum

number of polymorphic bands per assay were 18 and 60

bands, respectively (Table 4).

Based on the results, maximum genetic similarity

were observed between populations 17 (Shahrekord)

and 18 (Ahvaz) that have been at a subgroup and

most likely the origin of these two populations is

similar. In the end, 42 populations were exposed to

study with Cluster analysis of AFLP classified into 4

different main groups. Comparing the geographical

distribution and genetic diversity showed that there is

no correlation between them in some cases but it can

not be sataed definitely that there is no relationship

between the two of them. This lack of correlation have

been also reported in assessment of genetic diversity

in the samples of Ferula gummosa from Iran using

AFLP and RAPD markers (Khunani, 2008; Talebi

Kouyakhi et al., 2008).

Castellini et al., (1983) suggested that principal

components analysis as a complementary method with

cluster analysis lead to the optimum use of molecule

data. The comparison of plot with clustering graph has

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150 | Akbari et al

showed the appropriate distribution of populations

(Castellini et al., 2006). Using of molecular markers

and genetic diversity has been observed frequently in

the family Apiaceae (Zolala, 2008).

Khunani et al., (2008) indicated in the study of

genetic diversity from Ferulla gummosa of Different

regions of Iran with 10 AFLP primer combinations

that high genetic diversity between populations of

Ferulla gummosa can be identified with 10 AFLP

primers and also high genetic diversity of among the

populations of dill was observed in this research with

15 AFLP primer combinations (Khunani, 2008).

Kermani et al., (2006) used AFLP molecular markers

to study the genetic variation of 15 lines of Iranian

cumin (Cuminum cyminum L.) and 3 population of

Cuminum setifolium. In this study 149 scorable bands

were detected by 6 AFLP primer combinations that 73

numbers of them were polymorphic (49%). The

maximum number of polymorphic bands (20 bands)

and minimum number of polymorphic bands (3 bands)

were produced using the primer combinations (E-

AGT/M-CCG) and primer combinations (E-ACT/M-

CCG), respectively. Genetic diversity of Cuminum

cyminum L. (0/150) was more than Cuminum

setifolium (0.084), while the variation between these

species (0.163) was more than the diversity within

theirs. Drawn Dendrogram using the UPGMA could

completely separate these two species in the genetic

distance of 45٪. This study showed that genus of

Cuminum has relatively low level of diversity due to

being self-pollinated and it could be possible Cuminum

setifolium has been used as a new source of genetic

variation in crosses between species and transferring

desirable genes to cumin (Kermani et al., 2006).

It has been reported that the numbers of

amplification products in Withania somenifera

varied from 53 to 101 in E+ACG/M+CAT and

E+AAC/M+CAA primer combinations, respectively.

The percentage of polymorphism ranged from 79 in

the primer combinations of E+ACC/M+CTC and

E+AAC/M+CAA to 89 which were illustrated by

E+ACG/M+CAT with an average of 82% bands being

polymorphic (Negi et al., 2006).

In the case of dill and using populations that have

appropriate distribution throughout the country and

also 15 primer AFLP combination It can be concluded

with high confidence that this plant has a high level

diversity in the country. It is essential to investigate

phytochemical variation and the routes of metabolite

synthesis among the samples in order to introduce

appropriate varieties and perform breeding programs.

In conclusion, AFLP data sets showed a high level of

polymorphism among Iranian population of Iranian

dill reflecting their efficiency in the assessment of the

genetic diversity. These results can be used for

germplasma management and breeding.

Acknowledgements

We would like to thank the Institute of Medicinal

Plants (IMP), Karaj, Iran for their financial support

on this project.

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